From Data to Drug: How AI Transformed Clinical Trial Outcomes
Introduction: Drug discovery is a complicated, time-intensive, and expensive undertaking, fraught with vast uncertainty. Even with advancements in science and technology, many drug development programs continue to fail, mainly due to safety and efficacy issues. It takes over $2.5 billion and 8 to 10 years of R&D to bring a new drug to market. Yet fewer than 10% of candidates entering Phase 1 clinical trials ultimately receive FDA approval. Given these challenges, pharmaceutical companies are now pursuing alternative means to enhance the success rate and effectiveness of clinical trials. One such opportunity lies in using Artificial Intelligence (AI) to accelerate timelines, reduce costs, and improve decision-making throughout the trial lifecycle. Objective: A leading U.S. based biopharma client intended to minimize the lengthy timelines and high failure rates associated with traditional drug development. The client was interested in understanding how AI could improve the ef...